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Abdelakram Hafid
Researcher at University of Science and Technology Houari Boumediene
Publications - 15
Citations - 90
Abdelakram Hafid is an academic researcher from University of Science and Technology Houari Boumediene. The author has contributed to research in topics: Impedance cardiography & Computer science. The author has an hindex of 3, co-authored 8 publications receiving 46 citations. Previous affiliations of Abdelakram Hafid include University of Borås.
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Journal ArticleDOI
Full Impedance Cardiography Measurement Device Using Raspberry PI3 and System-on-Chip Biomedical Instrumentation Solutions
Abdelakram Hafid,Sara Benouar,Malika Kedir-Talha,Farhad Abtahi,Mokhtar Attari,Fernando Seoane +5 more
TL;DR: This paper presents a measurement system based on two System on Chip solutions and Raspberry PI, implementing both a full three-lead ECG recorder and an impedance cardiographer, for educational and research development purposes.
Journal ArticleDOI
Systematic Variability in ICG Recordings Results in ICG Complex Subtypes - Steps Towards the Enhancement of ICG Characterization.
Sara Benouar,Sara Benouar,Abdelakram Hafid,Abdelakram Hafid,Mokhtar Attari,Malika Kedir-Talha,Fernando Seoane,Fernando Seoane,Fernando Seoane +8 more
TL;DR: This study evaluated ICG recordings obtained from 10 volunteers and indicated that there are several different waveforms for the ABEXYOZ complex; there are up to five clearly distinct waveform types in addition to those that are typically reported.
Journal ArticleDOI
Simultaneous Recording of ICG and ECG Using Z-RPI Device with Minimum Number of Electrodes
Abdelakram Hafid,Sara Benouar,Malika Kedir-Talha,Mokhtar Attari,Fernando Seoane,Fernando Seoane,Fernando Seoane +6 more
TL;DR: The feasibility of recording an ICG signal simultaneously with electrocardiogram signal (ECG) using the same electrodes for both measurements, for a total of five electrodes rather than eight electrodes is presented.
Book ChapterDOI
First Steps Toward Automated Classification of Impedance Cardiography dZ/dt Complex Subtypes
Sara Benouar,Sara Benouar,Abdelakram Hafid,Abdelakram Hafid,Malika Kedir-Talha,Fernando Seoane,Fernando Seoane,Fernando Seoane +7 more
TL;DR: In this paper, artificial neural networks have been designed with two different configurations for pattern matching (PRANN) and tested to identify the 6 different ICG complex subtypes, one of the configurations implements a 6 classes classifier and the other implemented the divide and conquer approach classifying in two stages.
Journal ArticleDOI
A Novel Fiducial Point Extraction Algorithm to Detect C and D Points from the Acceleration Photoplethysmogram (CnD)
TL;DR: In this article , a fiducial point extraction algorithm was proposed to detect c and d points from the acceleration photoplethysmogram (APG), namely "CnD", which allows for the application of various pre-processing techniques, such as filtering, smoothing, and removing baseline drift.